Gesture Tool

ABSTRACT

Systems, methods and computer readable media are disclosed for a gesture tool. A capture device captures user movement and provides corresponding data to a gesture recognizer engine and an application. From that, the data is parsed to determine whether it satisfies one or more gesture filters, each filter corresponding to user-performed gesture. The data and the information about the filters is also sent to a gesture tool, which displays aspects of the data and filters. In response to user input corresponding to a change in a filter, the gesture tool sends an indication of such to the gesture recognizer engine and application, where that change occurs.

BACKGROUND OF THE INVENTION

Many computing applications such as computer games, multimediaapplications, office applications or the like use controls to allowusers to manipulate game characters or other aspects of an application.Typically such controls are input using, for example, controllers,remotes, keyboards, mice, or the like. Unfortunately, such controls canbe difficult to learn, thus creating a barrier between a user and suchgames and applications. Furthermore, such controls may be different thanactual game actions or other application actions for which the controlsare used. For example, a game control that causes a game character toswing a baseball bat may not correspond to an actual motion of swingingthe baseball bat.

SUMMARY OF THE INVENTION

Disclosed herein are systems and methods for a gesture tool. A gesturetool may be used by an application developer to visualize how usergesture input is being processed by a system, such as a gesturerecognizer engine (described in detail below). Using thosevisualizations, the developer may modify how the system processesgesture output (such as by tuning one or more gesture filter parametersof a filter in the gesture recognizer engine) to increase the quality ofuser experience.

In an embodiment, a recognizer engine comprises a base recognizer engineand at least one filter. A filter comprises a information about agesture and may comprise at least one corresponding parameter. Therecognizer engine provides to an application a filter and receives fromthat application at least one parameter that specifies the particularsof how that gesture is to be recognized by the recognizer engine.

In an embodiment, a system receives a series of image data from acamera. This camera may comprise a color camera (such as red-green-blueor RGB), a depth camera, and a three-dimensional (3D) camera. This datamay comprise separate depth and color images, a combined image thatincorporates depth and color information, or a parsed image whereobjects are identified, such as people that are skeletal mapped. Thisdata captures motions or poses made by at least one user. Based on thisimage data, the recognizer engine is able to parse gestures that theuser intends to convey. The recognizer engine detects that thelikelihood that the user has conveyed a gesture, and that the user hassatisfied any parameters, either default or application-determined,associated with the gesture for the application. The recognizer enginethen sends the confidence level that this has occurred to theapplication. In sending this confidence level, the recognizer engine mayalso send the application specifics of how the user conveyed the gesturefor further processing by the application.

The data is further sent to a gesture tool. The gesture tool displays avisual representation of the data. In an embodiment, this visualrepresentation comprises a list of those gesture filters used by theapplication, a list of parameters of a selected gesture filter of thelist, a graph of each output of the selected gesture filter over time,and the image data from the camera and a corresponding skeletal map. Inresponse to an adjustment of a value of a parameter via the visualrepresentation, that adjustment is sent to the application where thegesture filter is correspondingly adjusted. That adjusted filter is thenevaluated by the recognizer engine, and reflected in any outputsdisplayed by the gesture tool.

The foregoing is a summary and thus contains, by necessity,simplifications, generalizations and omissions of detail. Those skilledin the art will appreciate that the summary is illustrative only and isnot intended to be in any way limiting.

BRIEF DESCRIPTION OF THE DRAWINGS

The systems, methods, and computer readable media for a gesture tool inaccordance with this specification are further described with referenceto the accompanying drawings in which:

FIGS. 1A and 1B illustrate an example embodiment of a targetrecognition, analysis, and tracking system with a user playing a game.

FIG. 2 illustrates an example embodiment of a capture device that may beused in a target recognition, analysis, and tracking system.

FIG. 3A illustrates an example embodiment of a computing environmentthat may be used to interpret one or more gestures in a targetrecognition, analysis, and tracking system.

FIG. 3B illustrates another example embodiment of a computingenvironment that may be used to interpret one or more gestures in atarget recognition, analysis, and tracking system.

FIG. 4A illustrates a skeletal mapping of a user that has been generatedfrom the target recognition, analysis, and tracking system of FIG. 2.

FIG. 4B illustrates further details of the gesture recognizerarchitecture shown in FIG. 2.

FIGS. 5A and 5B illustrate how gesture filters may be stacked to createmore complex gesture filters.

FIGS. 6A, 6B, 6C, 6D, and 6E illustrate an example gesture that a user502 may make to signal for a “fair catch” in football video game.

FIGS. 7A, 7B, 7C, 7D, and 7E illustrate the example “fair catch” gestureof FIGS. 6A, 6B, 6C, 6D, and 6E as each frame of image data has beenparsed to produce a skeletal map of the user.

FIG. 8 illustrates further details of the gesture tool shown in FIG. 4B.

FIG. 9A illustrates an example architecture of a gesture tool operatingin conjunction with an application.

FIG. 9B illustrates another example architecture of a gesture tooloperating in conjunction with an application.

FIG. 10 illustrates exemplary operational procedures for a gesture tool.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

As will be described herein, a user may control an application executingon a computing environment such as a game console, a computer, or thelike by performing one or more gestures. According to one embodiment,the gestures may be received by, for example, a capture device. Forexample, the capture device may capture a depth image of a scene. In oneembodiment, the capture device may determine whether one or more targetsor objects in the scene corresponds to a human target such as the user.To determine whether a target or object in the scene corresponds a humantarget, each of the targets may be flood filled and compared to apattern of a human body model. Each target or object that matches thehuman body model may then be scanned to generate a skeletal modelassociated therewith. The skeletal model may then be provided to thecomputing environment such that the computing environment may track theskeletal model, render an avatar associated with the skeletal model, andmay determine which controls to perform in an application executing onthe computer environment based on, for example, gestures of the userthat have been recognized from the skeletal model. A gesture recognizerengine, the architecture of which is described more fully below, is usedto determine when a particular gesture has been made by the user.

FIGS. 1A and 1B illustrate an example embodiment of a configuration of atarget recognition, analysis, and tracking system 10 with a user 18playing a boxing game. In an example embodiment, the target recognition,analysis, and tracking system 10 may be used to recognize, analyze,and/or track a human target such as the user 18.

As shown in FIG. 1A, the target recognition, analysis, and trackingsystem 10 may include a computing environment 12. The computingenvironment 12 may be a computer, a gaming system or console, or thelike. According to an example embodiment, the computing environment 12may include hardware components and/or software components such that thecomputing environment 12 may be used to execute applications such asgaming applications, non-gaming applications, or the like.

As shown in FIG. 1A, the target recognition, analysis, and trackingsystem 10 may further include a capture device 20. The capture device 20may be, for example, a camera that may be used to visually monitor oneor more users, such as the user 18, such that gestures performed by theone or more users may be captured, analyzed, and tracked to perform oneor more controls or actions within an application, as will be describedin more detail below.

According to one embodiment, the target recognition, analysis, andtracking system 10 may be connected to an audiovisual device 16 such asa television, a monitor, a high-definition television (HDTV), or thelike that may provide game or application visuals and/or audio to a usersuch as the user 18. For example, the computing environment 12 mayinclude a video adapter such as a graphics card and/or an audio adaptersuch as a sound card that may provide audiovisual signals associatedwith the game application, non-game application, or the like. Theaudiovisual device 16 may receive the audiovisual signals from thecomputing environment 12 and may then output the game or applicationvisuals and/or audio associated with the audiovisual signals to the user18. According to one embodiment, the audiovisual device 16 may beconnected to the computing environment 12 via, for example, an S-Videocable, a coaxial cable, an HDMI cable, a DVI cable, a VGA cable, or thelike.

As shown in FIGS. 1A and 1B, the target recognition, analysis, andtracking system 10 may be used to recognize, analyze, and/or track ahuman target such as the user 18. For example, the user 18 may betracked using the capture device 20 such that the movements of user 18may be interpreted as controls that may be used to affect theapplication being executed by computer environment 12. Thus, accordingto one embodiment, the user 18 may move his or her body to control theapplication.

As shown in FIGS. 1A and 1B, in an example embodiment, the applicationexecuting on the computing environment 12 may be a boxing game that theuser 18 may be playing. For example, the computing environment 12 mayuse the audiovisual device 16 to provide a visual representation of aboxing opponent 22 to the user 18. The computing environment 12 may alsouse the audiovisual device 16 to provide a visual representation of aplayer avatar 24 that the user 18 may control with his or her movements.For example, as shown in FIG. 1B, the user 18 may throw a punch inphysical space to cause the player avatar 24 to throw a punch in gamespace. Thus, according to an example embodiment, the computerenvironment 12 and the capture device 20 of the target recognition,analysis, and tracking system 10 may be used to recognize and analyzethe punch of the user 18 in physical space such that the punch may beinterpreted as a game control of the player avatar 24 in game space.

Other movements by the user 18 may also be interpreted as other controlsor actions, such as controls to bob, weave, shuffle, block, jab, orthrow a variety of different power punches. Furthermore, some movementsmay be interpreted as controls that may correspond to actions other thancontrolling the player avatar 24. For example, the player may usemovements to end, pause, or save a game, select a level, view highscores, communicate with a friend, etc.

In example embodiments, the human target such as the user 18 may have anobject. In such embodiments, the user of an electronic game may beholding the object such that the motions of the player and the objectmay be used to adjust and/or control parameters of the game. Forexample, the motion of a player holding a racket may be tracked andutilized for controlling an on-screen racket in an electronic sportsgame. In another example embodiment, the motion of a player holding anobject may be tracked and utilized for controlling an on-screen weaponin an electronic combat game.

According to other example embodiments, the target recognition,analysis, and tracking system 10 may further be used to interpret targetmovements as operating system and/or application controls that areoutside the realm of games. For example, virtually any controllableaspect of an operating system and/or application may be controlled bymovements of the target such as the user 18.

FIG. 2 illustrates an example embodiment of the capture device 20 thatmay be used in the target recognition, analysis, and tracking system 10.According to an example embodiment, the capture device 20 may beconfigured to capture video with depth information including a depthimage that may include depth values via any suitable techniqueincluding, for example, time-of-flight, structured light, stereo image,or the like. According to one embodiment, the capture device 20 mayorganize the calculated depth information into “Z layers,” or layersthat may be perpendicular to a Z axis extending from the depth cameraalong its line of sight.

As shown in FIG. 2, the capture device 20 may include an image cameracomponent 22. According to an example embodiment, the image cameracomponent 22 may be a depth camera that may capture the depth image of ascene. The depth image may include a two-dimensional (2-D) pixel area ofthe captured scene where each pixel in the 2-D pixel area may representa length in, for example, centimeters, millimeters, or the like of anobject in the captured scene from the camera.

As shown in FIG. 2, according to an example embodiment, the image cameracomponent 22 may include an IR light component 24, a three-dimensional(3-D) camera 26, and an RGB camera 28 that may be used to capture thedepth image of a scene. For example, in time-of-flight analysis, the IRlight component 24 of the capture device 20 may emit an infrared lightonto the scene and may then use sensors (not shown) to detect thebackscattered light from the surface of one or more targets and objectsin the scene using, for example, the 3-D camera 26 and/or the RGB camera28. In some embodiments, pulsed infrared light may be used such that thetime between an outgoing light pulse and a corresponding incoming lightpulse may be measured and used to determine a physical distance from thecapture device 20 to a particular location on the targets or objects inthe scene. Additionally, in other example embodiments, the phase of theoutgoing light wave may be compared to the phase of the incoming lightwave to determine a phase shift. The phase shift may then be used todetermine a physical distance from the capture device to a particularlocation on the targets or objects.

According to another example embodiment, time-of-flight analysis may beused to indirectly determine a physical distance from the capture device20 to a particular location on the targets or objects by analyzing theintensity of the reflected beam of light over time via varioustechniques including, for example, shuttered light pulse imaging.

In another example embodiment, the capture device 20 may use astructured light to capture depth information. In such an analysis,patterned light (i.e., light displayed as a known pattern such as gridpattern or a stripe pattern) may be projected onto the scene via, forexample, the IR light component 24. Upon striking the surface of one ormore targets or objects in the scene, the pattern may become deformed inresponse. Such a deformation of the pattern may be captured by, forexample, the 3-D camera 26 and/or the RGB camera 28 and may then beanalyzed to determine a physical distance from the capture device to aparticular location on the targets or objects.

According to another embodiment, the capture device 20 may include twoor more physically separated cameras that may view a scene fromdifferent angles, to obtain visual stereo data that may be resolved togenerate depth information

The capture device 20 may further include a microphone 30. Themicrophone 30 may include a transducer or sensor that may receive andconvert sound into an electrical signal. According to one embodiment,the microphone 30 may be used to reduce feedback between the capturedevice 20 and the computing environment 12 in the target recognition,analysis, and tracking system 10. Additionally, the microphone 30 may beused to receive audio signals that may also be provided by the user tocontrol applications such as game applications, non-game applications,or the like that may be executed by the computing environment 12.

In an example embodiment, the capture device 20 may further include aprocessor 32 that may be in operative communication with the imagecamera component 22. The processor 32 may include a standardizedprocessor, a specialized processor, a microprocessor, or the like thatmay execute instructions that may include instructions for receiving thedepth image, determining whether a suitable target may be included inthe depth image, converting the suitable target into a skeletalrepresentation or model of the target, or any other suitableinstruction.

The capture device 20 may further include a memory component 34 that maystore the instructions that may be executed by the processor 32, imagesor frames of images captured by the 3-D camera or RGB camera, or anyother suitable information, images, or the like. According to an exampleembodiment, the memory component 34 may include random access memory(RAM), read only memory (ROM), cache, Flash memory, a hard disk, or anyother suitable storage component. As shown in FIG. 2, in one embodiment,the memory component 34 may be a separate component in communicationwith the image capture component 22 and the processor 32. According toanother embodiment, the memory component 34 may be integrated into theprocessor 32 and/or the image capture component 22.

As shown in FIG. 2, the capture device 20 may be in communication withthe computing environment 12 via a communication link 36. Thecommunication link 36 may be a wired connection including, for example,a USB connection, a Firewire connection, an Ethernet cable connection,or the like and/or a wireless connection such as a wireless 802.11b, g,a, or n connection. According to one embodiment, the computingenvironment 12 may provide a clock to the capture device 20 that may beused to determine when to capture, for example, a scene via thecommunication link 36.

Additionally, the capture device 20 may provide the depth informationand images captured by, for example, the 3-D camera 26 and/or the RGBcamera 28, and a skeletal model that may be generated by the capturedevice 20 to the computing environment 12 via the communication link 36.The computing environment 12 may then use the skeletal model, depthinformation, and captured images to, for example, recognize usergestures and in response control an application such as a game or wordprocessor. For example, as shown, in FIG. 2, the computing environment12 may include a gestures recognizer engine 190. The gestures recognizerengine 190 may include a collection of gesture filters, each comprisinginformation concerning a gesture that may be performed by the skeletalmodel (as the user moves). The data captured by the cameras 26, 28 anddevice 20 in the form of the skeletal model and movements associatedwith it may be compared to the gesture filters in the gesture recognizerengine 190 to identify when a user (as represented by the skeletalmodel) has performed one or more gestures. Those gestures may beassociated with various controls of an application. Thus, the computingenvironment 12 may use the gesture recognizer engine 190 to interpretmovements of the skeletal model and to control an application based onthe movements.

FIG. 3A illustrates an example embodiment of a computing environmentthat may be used to interpret one or more gestures in a targetrecognition, analysis, and tracking system. The computing environmentsuch as the computing environment 12 described above with respect toFIGS. 1A-2 may be a multimedia console 100, such as a gaming console. Asshown in FIG. 3A, the multimedia console 100 has a central processingunit (CPU) 101 having a level 1 cache 102, a level 2 cache 104, and aflash ROM (Read Only Memory) 106. The level 1 cache 102 and a level 2cache 104 temporarily store data and hence reduce the number of memoryaccess cycles, thereby improving processing speed and throughput. TheCPU 101 may be provided having more than one core, and thus, additionallevel 1 and level 2 caches 102 and 104. The flash ROM 106 may storeexecutable code that is loaded during an initial phase of a boot processwhen the multimedia console 100 is powered ON.

A graphics processing unit (GPU) 108 and a video encoder/video codec(coder/decoder) 114 form a video processing pipeline for high speed andhigh resolution graphics processing. Data is carried from the graphicsprocessing unit 108 to the video encoder/video codec 114 via a bus. Thevideo processing pipeline outputs data to an A/V (audio/video) port 140for transmission to a television or other display. A memory controller110 is connected to the GPU 108 to facilitate processor access tovarious types of memory 112, such as, but not limited to, a RAM (RandomAccess Memory).

The multimedia console 100 includes an I/O controller 120, a systemmanagement controller 122, an audio processing unit 123, a networkinterface controller 124, a first USB host controller 126, a second USBcontroller 128 and a front panel I/O subassembly 130 that are preferablyimplemented on a module 118. The USB controllers 126 and 128 serve ashosts for peripheral controllers 142(1)-142(2), a wireless adapter 148,and an external memory device 146 (e.g., flash memory, external CD/DVDROM drive, removable media, etc.). The network interface 124 and/orwireless adapter 148 provide access to a network (e.g., the Internet,home network, etc.) and may be any of a wide variety of various wired orwireless adapter components including an Ethernet card, a modem, aBluetooth module, a cable modem, and the like.

System memory 143 is provided to store application data that is loadedduring the boot process. A media drive 144 is provided and may comprisea DVD/CD drive, hard drive, or other removable media drive, etc. Themedia drive 144 may be internal or external to the multimedia console100. Application data may be accessed via the media drive 144 forexecution, playback, etc. by the multimedia console 100. The media drive144 is connected to the I/O controller 120 via a bus, such as a SerialATA bus or other high speed connection (e.g., IEEE 1394).

The system management controller 122 provides a variety of servicefunctions related to assuring availability of the multimedia console100. The audio processing unit 123 and an audio codec 132 form acorresponding audio processing pipeline with high fidelity and stereoprocessing. Audio data is carried between the audio processing unit 123and the audio codec 132 via a communication link. The audio processingpipeline outputs data to the A/V port 140 for reproduction by anexternal audio player or device having audio capabilities.

The front panel I/O subassembly 130 supports the functionality of thepower button 150 and the eject button 152, as well as any LEDs (lightemitting diodes) or other indicators exposed on the outer surface of themultimedia console 100. A system power supply module 136 provides powerto the components of the multimedia console 100. A fan 138 cools thecircuitry within the multimedia console 100.

The CPU 101, GPU 108, memory controller 110, and various othercomponents within the multimedia console 100 are interconnected via oneor more buses, including serial and parallel buses, a memory bus, aperipheral bus, and a processor or local bus using any of a variety ofbus architectures. By way of example, such architectures can include aPeripheral Component Interconnects (PCI) bus, PCI-Express bus, etc.

When the multimedia console 100 is powered ON, application data may beloaded from the system memory 143 into memory 112 and/or caches 102, 104and executed on the CPU 101. The application may present a graphicaluser interface that provides a consistent user experience whennavigating to different media types available on the multimedia console100. In operation, applications and/or other media contained within themedia drive 144 may be launched or played from the media drive 144 toprovide additional functionalities to the multimedia console 100.

The multimedia console 100 may be operated as a standalone system bysimply connecting the system to a television or other display. In thisstandalone mode, the multimedia console 100 allows one or more users tointeract with the system, watch movies, or listen to music. However,with the integration of broadband connectivity made available throughthe network interface 124 or the wireless adapter 148, the multimediaconsole 100 may further be operated as a participant in a larger networkcommunity.

When the multimedia console 100 is powered ON, a set amount of hardwareresources are reserved for system use by the multimedia consoleoperating system. These resources may include a reservation of memory(e.g., 16 MB), CPU and GPU cycles (e.g., 5%), networking bandwidth(e.g., 8 kbs), etc. Because these resources are reserved at system boottime, the reserved resources do not exist from the application's view.

In particular, the memory reservation preferably is large enough tocontain the launch kernel, concurrent system applications and drivers.The CPU reservation is preferably constant such that if the reserved CPUusage is not used by the system applications, an idle thread willconsume any unused cycles.

With regard to the GPU reservation, lightweight messages generated bythe system applications (e.g., popups) are displayed by using a GPUinterrupt to schedule code to render popup into an overlay. The amountof memory required for an overlay depends on the overlay area size andthe overlay preferably scales with screen resolution. Where a full userinterface is used by the concurrent system application, it is preferableto use a resolution independent of application resolution. A scaler maybe used to set this resolution such that the need to change frequencyand cause a TV resynch is eliminated.

After the multimedia console 100 boots and system resources arereserved, concurrent system applications execute to provide systemfunctionalities. The system functionalities are encapsulated in a set ofsystem applications that execute within the reserved system resourcesdescribed above. The operating system kernel identifies threads that aresystem application threads versus gaming application threads. The systemapplications are preferably scheduled to run on the CPU 101 atpredetermined times and intervals in order to provide a consistentsystem resource view to the application. The scheduling is to minimizecache disruption for the gaming application running on the console.

When a concurrent system application requires audio, audio processing isscheduled asynchronously to the gaming application due to timesensitivity. A multimedia console application manager (described below)controls the gaming application audio level (e.g., mute, attenuate) whensystem applications are active.

Input devices (e.g., controllers 142(1) and 142(2)) are shared by gamingapplications and system applications. The input devices are not reservedresources, but are to be switched between system applications and thegaming application such that each will have a focus of the device. Theapplication manager preferably controls the switching of input stream,without knowledge the gaming application's knowledge and a drivermaintains state information regarding focus switches. The cameras 26, 28and capture device 20 may define additional input devices for theconsole 100.

FIG. 3B illustrates another example embodiment of a computingenvironment 220 that may be the computing environment 12 shown in FIGS.1A-2 used to interpret one or more gestures in a target recognition,analysis, and tracking system. The computing system environment 220 isonly one example of a suitable computing environment and is not intendedto suggest any limitation as to the scope of use or functionality of thepresently disclosed subject matter. Neither should the computingenvironment 220 be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary operating environment 220. In some embodiments the variousdepicted computing elements may include circuitry configured toinstantiate specific aspects of the present disclosure. For example, theterm circuitry used in the disclosure can include specialized hardwarecomponents configured to perform function(s) by firmware or switches. Inother examples embodiments the term circuitry can include a generalpurpose processing unit, memory, etc., configured by softwareinstructions that embody logic operable to perform function(s). Inexample embodiments where circuitry includes a combination of hardwareand software, an implementer may write source code embodying logic andthe source code can be compiled into machine readable code that can beprocessed by the general purpose processing unit. Since one skilled inthe art can appreciate that the state of the art has evolved to a pointwhere there is little difference between hardware, software, or acombination of hardware/software, the selection of hardware versussoftware to effectuate specific functions is a design choice left to animplementer. More specifically, one of skill in the art can appreciatethat a software process can be transformed into an equivalent hardwarestructure, and a hardware structure can itself be transformed into anequivalent software process. Thus, the selection of a hardwareimplementation versus a software implementation is one of design choiceand left to the implementer.

In FIG. 3B, the computing environment 220 comprises a computer 241,which typically includes a variety of computer readable media. Computerreadable media can be any available media that can be accessed bycomputer 241 and includes both volatile and nonvolatile media, removableand non-removable media. The system memory 222 includes computer storagemedia in the form of volatile and/or nonvolatile memory such as readonly memory (ROM) 223 and random access memory (RAM) 260. A basicinput/output system 224 (BIOS), containing the basic routines that helpto transfer information between elements within computer 241, such asduring start-up, is typically stored in ROM 223. RAM 260 typicallycontains data and/or program modules that are immediately accessible toand/or presently being operated on by processing unit 259. By way ofexample, and not limitation, FIG. 3B illustrates operating system 225,application programs 226, other program modules 227, and program data228.

The computer 241 may also include other removable/non-removable,volatile/nonvolatile computer storage media. By way of example only,FIG. 3B illustrates a hard disk drive 238 that reads from or writes tonon-removable, nonvolatile magnetic media, a magnetic disk drive 239that reads from or writes to a removable, nonvolatile magnetic disk 254,and an optical disk drive 240 that reads from or writes to a removable,nonvolatile optical disk 253 such as a CD ROM or other optical media.Other removable/non-removable, volatile/nonvolatile computer storagemedia that can be used in the exemplary operating environment include,but are not limited to, magnetic tape cassettes, flash memory cards,digital versatile disks, digital video tape, solid state RAM, solidstate ROM, and the like. The hard disk drive 238 is typically connectedto the system bus 221 through an non-removable memory interface such asinterface 234, and magnetic disk drive 239 and optical disk drive 240are typically connected to the system bus 221 by a removable memoryinterface, such as interface 235.

The drives and their associated computer storage media discussed aboveand illustrated in FIG. 3B, provide storage of computer readableinstructions, data structures, program modules and other data for thecomputer 241. In FIG. 3B, for example, hard disk drive 238 isillustrated as storing operating system 258, application programs 257,other program modules 256, and program data 255. Note that thesecomponents can either be the same as or different from operating system225, application programs 226, other program modules 227, and programdata 228. Operating system 258, application programs 257, other programmodules 256, and program data 255 are given different numbers here toillustrate that, at a minimum, they are different copies. A user mayenter commands and information into the computer 241 through inputdevices such as a keyboard 251 and pointing device 252, commonlyreferred to as a mouse, trackball or touch pad. Other input devices (notshown) may include a microphone, joystick, game pad, satellite dish,scanner, or the like. These and other input devices are often connectedto the processing unit 259 through a user input interface 236 that iscoupled to the system bus, but may be connected by other interface andbus structures, such as a parallel port, game port or a universal serialbus (USB). The cameras 26, 28 and capture device 20 may defineadditional input devices for the console 100. A monitor 242 or othertype of display device is also connected to the system bus 221 via aninterface, such as a video interface 232. In addition to the monitor,computers may also include other peripheral output devices such asspeakers 244 and printer 243, which may be connected through a outputperipheral interface 233.

The computer 241 may operate in a networked environment using logicalconnections to one or more remote computers, such as a remote computer246. The remote computer 246 may be a personal computer, a server, arouter, a network PC, a peer device or other common network node, andtypically includes many or all of the elements described above relativeto the computer 241, although only a memory storage device 247 has beenillustrated in FIG. 3B. The logical connections depicted in FIG. 3Binclude a local area network (LAN) 245 and a wide area network (WAN)249, but may also include other networks. Such networking environmentsare commonplace in offices, enterprise-wide computer networks, intranetsand the Internet.

When used in a LAN networking environment, the computer 241 is connectedto the LAN 245 through a network interface or adapter 237. When used ina WAN networking environment, the computer 241 typically includes amodem 250 or other means for establishing communications over the WAN249, such as the Internet. The modem 250, which may be internal orexternal, may be connected to the system bus 221 via the user inputinterface 236, or other appropriate mechanism. In a networkedenvironment, program modules depicted relative to the computer 241, orportions thereof, may be stored in the remote memory storage device. Byway of example, and not limitation, FIG. 3B illustrates remoteapplication programs 248 as residing on memory device 247. It will beappreciated that the network connections shown are exemplary and othermeans of establishing a communications link between the computers may beused.

FIG. 4A depicts an example skeletal mapping of a user that may begenerated from the capture device 20. In this embodiment, a variety ofjoints and bones are identified: each hand 302, each forearm 304, eachelbow 306, each bicep 308, each shoulder 310, each hip 312, each thigh314, each knee 316, each foreleg 318, each foot 320, the head 322, thetorso 324, the top 326 and bottom 328 of the spine, and the waist 330.Where more points are tracked, additional features may be identified,such as the bones and joints of the fingers or toes, or individualfeatures of the face, such as the nose and eyes.

Through moving his body, a user may create gestures. A gesture comprisesa motion or pose by a user that may be captured as image data and parsedfor meaning. A gesture may be dynamic, comprising a motion, such asmimicking throwing a ball. A gesture may be a static pose, such asholding one's crossed forearms 304 in front of his torso 324. A gesturemay also incorporate props, such as by swinging a mock sword. A gesturemay comprise more than one body part, such as clapping the hands 302together, or a subtler motion, such as pursing one's lips.

Gestures may be used for input in a general computing context. Forinstance, various motions of the hands 302 or other body parts maycorrespond to common system wide tasks such as navigate up or down in ahierarchical list, open a file, close a file, and save a file. Gesturesmay also be used in a video-game-specific context, depending on thegame. For instance, with a driving game, various motions of the hands302 and feet 320 may correspond to steering a vehicle in a direction,shifting gears, accelerating, and breaking.

A user may generate a gesture that corresponds to walking or running, bywalking or running in place himself The user may alternately lift anddrop each leg 312-320 to mimic walking without moving. The system mayparse this gesture by analyzing each hip 312 and each thigh 314. A stepmay be recognized when one hip-thigh angle (as measured relative to avertical line, wherein a standing leg has a hip-thigh angle of 0°, and aforward horizontally extended leg has a hip-thigh angle of 90°) exceedsa certain threshold relative to the other thigh. A walk or run may berecognized after some number of consecutive steps by alternating legs.The time between the two most recent steps may be thought of as aperiod. After some number of periods where that threshold angle is notmet, the system may determine that the walk or running gesture hasceased.

Given a “walk or run” gesture, an application may set values forparameters associated with this gesture. These parameters may includethe above threshold angle, the number of steps required to initiate awalk or run gesture, a number of periods where no step occurs to end thegesture, and a threshold period that determines whether the gesture is awalk or a run. A fast period may correspond to a run, as the user willbe moving his legs quickly, and a slower period may correspond to awalk.

A gesture may be associated with a set of default parameters at firstthat the application may override with its own parameters. In thisscenario, an application is not forced to provide parameters, but mayinstead use a set of default parameters that allow the gesture to berecognized in the absence of application-defined parameters.

There are a variety of outputs that may be associated with the gesture.There may be a baseline “yes or no” as to whether a gesture isoccurring. There also may be a confidence level, which corresponds tothe likelihood that the user's tracked movement corresponds to thegesture. This could be a linear scale that ranges over floating pointnumbers between 0 and 1, inclusive. Wherein an application receivingthis gesture information cannot accept false-positives as input, it mayuse only those recognized gestures that have a high confidence level,such as at least 0.95. Where an application must recognize everyinstance of the gesture, even at the cost of false-positives, it may usegestures that have at least a much lower confidence level, such as thosemerely greater than 0.2. The gesture may have an output for the timebetween the two most recent steps, and where only a first step has beenregistered, this may be set to a reserved value, such as −1 (since thetime between any two steps must be positive). The gesture may also havean output for the highest thigh angle reached during the most recentstep.

Another exemplary gesture is a “heel lift jump.” In this, a user maycreate the gesture by raising his heels off the ground, but keeping histoes planted. Alternatively, the user may jump into the air where hisfeet 320 leave the ground entirely. The system may parse the skeletonfor this gesture by analyzing the angle relation of the shoulders 310,hips 312 and knees 316 to see if they are in a position of alignmentequal to standing up straight. Then these points and upper 326 and lower328 spine points may be monitored for any upward acceleration. Asufficient combination of acceleration may trigger a jump gesture.

Given this “heel lift jump” gesture, an application may set values forparameters associated with this gesture. The parameters may include theabove acceleration threshold, which determines how fast some combinationof the user's shoulders 310, hips 312 and knees 316 must move upward totrigger the gesture, as well as a maximum angle of alignment between theshoulders 310, hips 312 and knees 316 at which a jump may still betriggered.

The outputs may comprise a confidence level, as well as the user's bodyangle at the time of the jump.

Setting parameters for a gesture based on the particulars of theapplication that will receive the gesture is important in accuratelyidentifying gestures. Properly identifying gestures and the intent of auser greatly helps in creating a positive user experience. Where agesture recognizer system is too sensitive, and even a slight forwardmotion of the hand 302 is interpreted as a throw, the user may becomefrustrated because gestures are being recognized where he has no intentto make a gesture, and thus, he lacks control over the system. Where agesture recognizer system is not sensitive enough, the system may notrecognize conscious attempts by the user to make a throwing gesture,frustrating him in a similar manner. At either end of the sensitivityspectrum, the user becomes frustrated because he cannot properly provideinput to the system.

Another parameter to a gesture may be a distance moved. Where a user'sgestures control the actions of an avatar in a virtual environment, thatavatar may be arm's length from a ball. If the user wishes to interactwith the ball and grab it, this may require the user to extend his arm302-310 to full length while making the grab gesture. In this situation,a similar grab gesture where the user only partially extends his arm302-310 may not achieve the result of interacting with the ball.

A gesture or a portion thereof may have as a parameter a volume of spacein which it must occur. This volume of space may typically be expressedin relation to the body where a gesture comprises body movement. Forinstance, a football throwing gesture for a right-handed user may berecognized only in the volume of space no lower than the right shoulder310 a, and on the same side of the head 322 as the throwing arm 302a-310 a. It may not be necessary to define all bounds of a volume, suchas with this throwing gesture, where an outer bound away from the bodyis left undefined, and the volume extends out indefinitely, or to theedge of scene that is being monitored.

FIG. 4B provides further details of one exemplary embodiment of thegesture recognizer engine 190 of FIG. 2. As shown, the gesturerecognizer engine 190 may comprise at least one filter 418 to determinea gesture or gestures. A filter 418 comprises information defining agesture 426 (hereinafter referred to as a “gesture”) along withparameters 428, or metadata, for that gesture. For instance, a throw,which comprises motion of one of the hands from behind the rear of thebody to past the front of the body, may be implemented as a gesture 426comprising information representing the movement of one of the hands ofthe user from behind the rear of the body to past the front of the body,as that movement would be captured by the depth camera. Parameters 428may then be set for that gesture 426. Where the gesture 426 is a throw,a parameter 428 may be a threshold velocity that the hand has to reach,a distance the hand must travel (either absolute, or relative to thesize of the user as a whole), and a confidence rating by the recognizerengine that the gesture occurred. These parameters 428 for the gesture426 may vary between applications, between contexts of a singleapplication, or within one context of one application over time.

Filters may be modular or interchangeable. In an embodiment, a filterhas a number of inputs, each of those inputs having a type, and a numberof outputs, each of those outputs having a type. In this situation, afirst filter may be replaced with a second filter that has the samenumber and types of inputs and outputs as the first filter withoutaltering any other aspect of the recognizer engine architecture. Forinstance, there may be a first filter for driving that takes as inputskeletal data and outputs a confidence that the gesture associated withthe filter is occurring and an angle of steering. Where one wishes tosubstitute this first driving filter with a second drivingfilter—perhaps because the second driving filter is more efficient andrequires fewer processing resources—one may do so by simply replacingthe first filter with the second filter so long as the second filter hasthose same inputs and outputs—one input of skeletal data type, and twooutputs of confidence type and angle type.

A filter need not have a parameter. For instance, a “user height” filterthat returns the user's height may not allow for any parameters that maybe tuned. An alternate “user height” filter may have tunableparameters—such as to whether to account for a user's footwear,hairstyle, headwear and posture in determining the user's height.

Inputs to a filter may comprise things such as joint data about a user'sjoint position, like angles formed by the bones that meet at the joint,RGB color data from the scene, and the rate of change of an aspect ofthe user. Outputs from a filter may comprise things such as theconfidence that a given gesture is being made, the speed at which agesture motion is made, and a time at which a gesture motion is made.

A context may be a cultural context, and it may be an environmentalcontext. A cultural context refers to the culture of a user using asystem. Different cultures may use similar gestures to impart markedlydifferent meanings. For instance, an American user who wishes to tellanother user to “look” or “use his eyes” may put his index finger on hishead close to the distal side of his eye. However, to an Italian user,this gesture may be interpreted as a reference to the mafia.

Similarly, there may be different contexts among different environmentsof a single application. Take a first-person shooter game that involvesoperating a motor vehicle. While the user is on foot, making a fist withthe fingers towards the ground and extending the fist in front and awayfrom the body may represent a punching gesture. While the user is in thedriving context, that same motion may represent a “gear shifting”gesture. There may also be one or more menu environments, where the usercan save his game, select among his character's equipment or performsimilar actions that do not comprise direct game-play. In thatenvironment, this same gesture may have a third meaning, such as toselect something or to advance to another screen.

The gesture recognizer engine 190 may have a base recognizer engine 416that provides functionality to a gesture filter 418. In an embodiment,the functionality that the recognizer engine 416 implements includes aninput-over-time archive that tracks recognized gestures and other input,a Hidden Markov Model implementation (where the modeled system isassumed to be a Markov process—one where a present state encapsulatesany past state information necessary to determine a future state, so noother past state information must be maintained for this purpose—withunknown parameters, and hidden parameters are determined from theobservable data), as well as other functionality required to solveparticular instances of gesture recognition.

Filters 418 are loaded and implemented on top of the base recognizerengine 416 and can utilize services provided by the engine 416 to allfilters 418. In an embodiment, the base recognizer engine 416 processesreceived data to determine whether it meets the requirements of anyfilter 418. Since these provided services, such as parsing the input,are provided once by the base recognizer engine 416 rather than by eachfilter 418, such a service need only be processed once in a period oftime as opposed to once per filter 418 for that period, so theprocessing required to determine gestures is reduced.

An application may use the filters 418 provided by the recognizer engine190, or it may provide its own filter 418, which plugs in to the baserecognizer engine 416. In an embodiment, all filters 418 have a commoninterface to enable this plug-in characteristic. Further, all filters418 may utilize parameters 428, so a single gesture tool as describedbelow may be used to debug and tune the entire filter system 418.

These parameters 428 may be tuned for an application or a context of anapplication by a gesture tool 420. In an embodiment, the gesture tool420 comprises a plurality of sliders 422, each slider 422 correspondingto a parameter 428, as well as a pictoral representation of a body 424.As a parameter 428 is adjusted with a corresponding slider 422, the body424 may demonstrate both actions that would be recognized as the gesturewith those parameters 428 and actions that would not be recognized asthe gesture with those parameters 428, identified as such. Thisvisualization of the parameters 428 of gestures provides an effectivemeans to both debug and fine tune a gesture.

FIG. 5 depicts more complex gestures or filters 418 created from stackedgestures or filters 418. Gestures can stack on each other. That is, morethan one gesture may be expressed by a user at a single time. Forinstance, rather than disallowing any input but a throw when a throwinggesture is made, or requiring that a user remain motionless save for thecomponents of the gesture (e.g. stand still while making a throwinggesture that involves only one arm). Where gestures stack, a user maymake a jumping gesture and a throwing gesture simultaneously, and bothof these gestures will be recognized by the gesture engine.

FIG. 5A depicts a simple gesture filter 418 according to the stackingparadigm. The IFilter filter 502 is a basic filter 418 that may be usedin every gesture filter. IFilter 502 takes user position data 504 andoutputs a confidence level 506 that a gesture has occurred. It alsofeeds that position data 504 into a SteeringWheel filter 508 that takesit as an input and outputs an angle to which the user is steering (e.g.40 degrees to the right of the user's current bearing) 510.

FIG. 5B depicts a more complex gesture that stacks filters 418 onto thegesture filter of FIG. 5A. In addition to IFilter 502 and SteeringWheel508, there is an ITracking filter 512 that receives position data 504from IFilter 502 and outputs the amount of progress the user has madethrough a gesture 514. ITracking 512 also feeds position data 504 toGreaseLightning 516 and EBrake 518, which are filters 418 regardingother gestures that may be made in operating a vehicle, such as usingthe emergency brake.

FIG. 6 depicts an example gesture that a user 602 may make to signal fora “fair catch” in a football video game. These figures depict the userat points in time, with FIG. 6A being the first point in time, and FIG.6E being the last point in time. Each of these figures may correspond toa snapshot or frame of image data as captured by a depth camera 402,though not necessarily consecutive frames of image data, as the depthcamera 402 may be able to capture frames more rapidly than the user maycover the distance. For instance, this gesture may occur over a periodof 3 seconds, and where a depth camera captures data at 40 frames persecond, it would capture 60 frames of image data while the user 602 madethis fair catch gesture.

In FIG. 6A, the user 602 begins with his arms 604 down at his sides. Hethen raises them up and above his shoulders as depicted in FIG. 6B andthen further up, to the approximate level of his head, as depicted inFIG. 6C. From there, he lowers his arms 604 to shoulder level, asdepicted in FIG. 6D, and then again raises them up, to the approximatelevel of his head, as depicted in FIG. 6E. Where a system captures thesepositions by the user 602 without any intervening position that maysignal that the gesture is cancelled, or another gesture is being made,it may have the fair catch gesture filter output a high confidence levelthat the user 602 made the fair catch gesture.

FIG. 7 depicts the example “fair catch” gesture of FIG. 5 as each frameof image data has been parsed to produce a skeletal map of the user. Thesystem, having produced a skeletal map from the depth image of the user,may now determine how that user's body moves over time, and from that,parse the gesture.

In FIG. 7A, the user's shoulders 310, are above his elbows 306, which inturn are above his hands 302. The shoulders 310, elbows 306 and hands302 are then at a uniform level in FIG. 7B. The system then detects inFIG. 7C that the hands 302 are above the elbows, which are above theshoulders 3 10. In FIG. 7D, the user has returned to the position ofFIG. 7B, where the shoulders 310, elbows 306 and hands 302 are at auniform level. In the final position of the gesture, shown in FIG. 7E,the user returns to the position of FIG. 7C, where the hands 302 areabove the elbows, which are above the shoulders 310.

While the capture device 20 captures a series of still images, such thatin any one image the user appears to be stationary, the user is movingin the course of performing this gesture (as opposed to a stationarygesture, as discussed supra). The system is able to take this series ofposes in each still image, and from that determine the confidence levelof the moving gesture that the user is making.

In performing the gesture, a user is unlikely to be able to create anangle as formed by his right shoulder 310 a, right elbow 306 a and righthand 302 a of, for example, between 140° and 145°. So, the applicationusing the filter 418 for the fair catch gesture 426 may tune theassociated parameters 428 to best serve the specifics of theapplication. For instance, the positions in FIGS. 7C and 7E may berecognized any time the user has his hands 302 above his shoulders 310,without regard to elbow 306 position. A set of parameters that are morestrict may require that the hands 302 be above the head 310 and that theelbows 306 be both above the shoulders 310 and between the head 322 andthe hands 302. Additionally, the parameters 428 for a fair catch gesture426 may require that the user move from the position of FIG. 7A throughthe position of FIG. 7E within a specified period of time, such as 1.5seconds, and if the user takes more than 1.5 seconds to move throughthese positions, it will not be recognized as the fair catch 418, and avery low confidence level may be output.

FIG. 8 illustrates an exemplary embodiment of the gesture tool 420 shownin FIG. 4B.

Developing applications designed for gesture control may be cumbersome.To properly debug such an application, some portion of the screen mustusually be reserved for visualization of the data captured by thecapture device, such as by a picture-in-picture display. This consumesvital screen real estate as well as computation time and resources fromthe application.

The gesture tool, when running on a separate computing device, mayoff-load burden of visualizing camera input from the computing deviceexecuting the application. The gesture tool also permits the rapidrun-time iteration required for efficient gesture tuning. The gesturetool further provides a capability for recording and playing back datacaptured by the capture device for “off-line” gesture debugging. Thegesture tool also provides a common language for all gesture-monitoringfilters, which promotes modularity and the reuse of gesture filtersbetween applications.

In an embodiment, a list of filters 418 processed by the recognizerengine 190 for an application is displayed in area 802. Additionally,image data is displayed in area 808. In an embodiment, this image datacomprises color image data of a user 18 captured by capture device 20overlaid with a skeletal map 812 of that user, generated from that colorimage data.

In response to selection of a gesture filter listed in area 802, detailsfor parameters of that gesture filter are listed in area 804, along withuser interface elements that allow those parameters to be adjusted. Forinstance, where the “heel lift jump” gesture filter is selected in area802, area 804 displays the “acceleration threshold” and “maximum angle”parameters for that filter. The acceleration threshold parameterdetermines how fast some combination of the user's shoulders 310, hips312 and knees 316 must move upward to trigger the gesture. The maximumangle parameter comprises the maximum angle of alignment between theshoulders 310, hips 312 and knees 316 at which a jump may still betriggered. In response to input to adjust a parameter, that informationis sent to gesture recognizer engine 190, where the parameter isadjusted. That is, the value for that parameter in the particulargesture filter is modified to the new value entered with the gesturetool. This gesture filter with an adjusted parameter is then evaluatedby the gesture recognizer engine and information about that is sent backto the gesture tool 420 as before.

In an embodiment, those parts of the skeletal mapping that are used inevaluating a gesture filter are highlighted. For instance, where thegesture tool is focused on the “heel lift gesture,” the user's shoulders310, hips 312 and knees 316 may be highlighted in the skeleton map. Inan embodiment, this comprises displaying those portions of the skeletonmap in a different color than the rest of the skeleton map. In anembodiment, this comprises encircling or otherwise setting off thoseportions of the skeleton map from the rest of the skeleton map.

In an embodiment, area 806 displays a graph of at least one output ofthe selected gesture filter over time. In an embodiment where theselected gesture filter has multiple outputs, such as a confidence leveland an acceleration, each output may be graphed, and set off, such aswith a different color, or different style of line (e.g. solid, dotted,dashed).

FIG. 9A illustrates an example architecture of a gesture tool operatingin conjunction with an application. In this exemplary architecture,gesture tool 420 is executed on computing environment 902 andcommunicates with gesture recognizer engine 190, which is executed oncomputing environment 12, across communications network 904. Computingenvironment 12 communicates with capture device 20. The gesture tooldisplay is displayed on display device 16 a, and the visual output of anapplication executing on computing environment 12 is displayed ondisplay device 16 b. In another embodiment, both the visual output ofgesture tool 420 and an application executing on computing environment12 are displayed on the same display device 16.

In an embodiment, the gesture tool and the application communicatethrough a gesture tool conduit, which may be a self-contained library ofcode. An application may be developed with the gesture tool conduit, andas a result, accept communications requests from the gesture tool, andthen send and receive data from the gesture tool.

In an embodiment, the gesture tool conduit provides a simple interfacefor communication that allows an application to send images representingthe most recent color, depth, and infrared (IR) images received from thecapture device. The gesture tool may display this data using a varietyof visualizers from which a user of the gesture tool may select. Inaddition, the gesture tool conduit may provide a means for theapplication to add connotations to these images in the form of points,lines, geometric shapes, text, or other markers. These connotations maybe displayed by the gesture tool, providing the user of the gesture toolwith a self-contained view into the capture device data, withapplication-defined information overlays.

Additionally, the gesture tool conduit may provide a simple interfacewith which to register application variables with the gesture tool, suchthat the gesture tool can then display ad-hoc user interface elements tomonitor and edit these values on the fly. In this way, the gesture toolmay serve as an application-defined gesture filter monitoring and tuningapparatus, taking on those properties determined by the applicationitself. The gesture tuner may also automate the process of saving andloading snapshots of these application-defined gesture filterparameters, allowing a user of the gesture tool to edit those parametersand save the results for later use.

FIG. 9B illustrates another example architecture of a gesture tooloperating in conjunction with an application. In this exemplaryarchitecture, both gesture tool 420 and gesture recognizer engine 190execute on computing environment 12. Computing environment 12communicates with capture device 20. The visual output of both thegesture tool 420 and an application executing on computing environment12 that gesture tool is used to adjust are displayed on display device16. In an embodiment, computing environment 12 sends visual output to aplurality of display devices 16, and the visual output of the gesturetool 420 is sent to a separate display device 16 than the visual outputof the application.

FIG. 10 illustrates exemplary operational procedures for a gesture tool.

Operation 1002 depicts receiving data captured by a capture device, thedata comprising information about user position or movement. The capturedevice may capture a scene that contains all of the user, such as fromthe floor to the ceiling and to the wall on each side of a room at thedistance in which the user is located. The capture device may alsocapture a scene that contains only part of the user, such as the userfrom the abdomen up as he or she sits at a desk. The capture device mayalso capture an object controlled by the user, such as a prop camerathat the user holds in his or her hand.

In an embodiment, the data is received as the capture device capturesthe data. In an embodiment, the data is received from a storage locationwhere the data is stored as it is captured.

In an embodiment, the data comprises at least one of skeletal data,visible color data, infra-red color data, or depth data. In someembodiments, the data may comprise a combination of two or more of thesetypes of data.

Operation 1004 depicts displaying a visual output of the application.This may comprise the visual output of the application as it wouldnormally be displayed, were the gesture tool not present.

Operation 1006 depicts displaying a visual representation of at leastone aspect of the user data. In an embodiment, this comprises displayinga list of gesture filters associated with the application. In anembodiment, this comprises displaying at least one parameter for aselected gesture filter, the selected gesture being drawn from the listof gesture filters. In an embodiment, at least one displayed parameterhas an adjustable value, range of values, or upper or lower bound.

In an embodiment, this comprises displaying the data captured by thecapture device. This may comprise displaying color data of the user.Alternatively, this may comprise displaying skeletal mapping datacorresponding to the color data. Still further, this may comprisedisplaying a combination of different types of data. For example, boththe color data and the skeletal map data may be displayed. One type ofdata may be overlaid with the other. For example, the skeletal map maybe overlaid on the color data. In an embodiment, the parts of theskeletal map that correspond to the selected gesture filter areindicated, such as by being displayed with a different color than therest of the skeletal map.

In an embodiment, displaying a visual representation comprisesdisplaying a graph of at least one output of the gesture filter overtime.

The visual representation and the visual output may be displayed onseparate display devices. Alternatively, the visual representation andthe visual output may be displayed on the same display device. In anembodiment, they are displayed on the same display device throughpicture-in-picture or a split screen.

Operation 1008 depicts receiving, at the user interface, a change to aparameter of the gesture filter of the application. This may occur, forexample, where there is a text entry box associated with the parameterdisplayed in the visual representation, by receiving a new value in thetext entry box

Operation 1010 depicts altering the gesture filter corresponding to thereceived change. In an embodiment, this alteration is communicated tothe gesture recognizer engine where it is then communicated to theapplication, processed by the application, stored, and altered at thegesture recognizer engine, so that successive data from the capturedevice will be evaluated with the altered gesture filter.

In an embodiment, the received change is received from the visualrepresentation across a communications network.

Optional operation 1012 depicts storing the data captured by the capturedevice. The data may be stored for later evaluation of gesture filtersagainst it. For instance, the data may comprise a prime example of auser performing a heel lift jump, such that the “heel lift jump” gesturefilter should always output a high confidence level when evaluating thisdata no matter how the parameters are altered. This prime example may bestored so that whenever the “heel lift jump” gesture filter has analtered parameter, the stored data may be fun through the modifiedgesture filter to evaluate how well that modified filter “recognizes”the prime example of the heal lift jump.

Optional operation 1014 depicts adjusting the rate or direction ofdisplay of the visual representation. In an embodiment, this comprisesreversing through the user data and its corresponding visualrepresentation at normal, slow, or fast speed. In an embodiment, thiscomprises pausing the visual representation at a point in the data. Inan embodiment, this comprises advancing through the data and itscorresponding visual representation at a slower-than-normal speed. In anembodiment where the data is stored, or where the data has beenpreviously rewound, this comprises advancing through the data and itscorresponding visual representation at a fast speed.

Conclusion

While the present disclosure has been described in connection with thepreferred aspects, as illustrated in the various figures, it isunderstood that other similar aspects may be used or modifications andadditions may be made to the described aspects for performing the samefunction of the present disclosure without deviating therefrom.Therefore, the present disclosure should not be limited to any singleaspect, but rather construed in breadth and scope in accordance with theappended claims. For example, the various procedures described hereinmay be implemented with hardware or software, or a combination of both.Thus, the methods and apparatus of the disclosed embodiments, or certainaspects or portions thereof, may take the form of program code (i.e.,instructions) embodied in tangible media, such as floppy diskettes,CD-ROMs, hard drives, or any other machine-readable storage medium. Whenthe program code is loaded into and executed by a machine, such as acomputer, the machine becomes an apparatus configured for practicing thedisclosed embodiments. In addition to the specific implementationsexplicitly set forth herein, other aspects and implementations will beapparent to those skilled in the art from consideration of thespecification disclosed herein. It is intended that the specificationand illustrated implementations be considered as examples only.

1. A computer system, comprising: a processor; a tool executing on theprocessor that facilitates the adjustment of parameters of a gesturefilter of an application that is designed to recognize whether a user ofthe application has performed a particular gesture from data comprisinginformation about position or movement of the user, the tool operatingto: receive data captured by a capture device, the data comprisinginformation representing user position or movement; display a visualrepresentation of the position or movement represented by the receiveddata; display a representation of an output of the gesture filter inresponse to the received data; receive, via a user interface of thedisplay, a change to a parameter of the gesture filter of theapplication; and alter the gesture filter according to the receivedchange.
 2. The system of claim 1, the tool further operating to: receivethe change from the visual representation across a communicationsnetwork.
 3. The system of claim 1 wherein the visual representation ofat least one aspect of the user data is further comprises a listcomprising at least one gesture filter associated with the application.4. The system of claim 3 wherein the tool operating to display a visualrepresentation is further operating to, in response to user selection ofa gesture filter from the list, displaying at least one adjustableparameter of the selected gesture filter.
 5. The system of claim 3wherein the tool configured to display a visual representation isfurther configured to display a skeletal map associated with the data,and in response to user selection of a gesture filter from the list,display an indication of at least one part of the skeletal mapassociated with the selected gesture filter.
 6. The system of claim 3wherein the tool configured to display a visual representation isfurther configured to, in response to user selection of a gesture filterfrom the list, display at least one output of the selected gesturefilter.
 7. The system of claim 3 wherein at least one output isdisplayed as a graph of a value of the output over time.
 8. The systemof claim 3 wherein each gesture filter of the list is specified by theapplication.
 9. The system of claim 1 wherein the user data is recorded,the tool further operating to: adjust the rate or direction of displayof the visual representation.
 10. A method for altering visualizedparameters for a gesture filter of an application, comprising: receivingdata captured by a capture device, the data comprising information aboutuser position or movement; displaying a visual output of theapplication; displaying a visual representation of at least one aspectof the user data; receiving, via a user interface of the display, achange to a parameter of the gesture filter of the application; andaltering the gesture filter corresponding to the received change. 11.The method of claim 10 wherein the data is either received from thecapture device as it is captured, or the data is received from a storagelocation where the data is stored as it is captured.
 12. The method ofclaim 10 wherein the visual representation and the visual output areeither displayed on a single display device or displayed on separatedisplay devices.
 13. The method of claim 12 wherein the wherein thevisual representation and the visual output are either displayed on asingle display device through either a split-screen orpicture-in-picture.
 14. The method of claim 10 wherein the datacomprises at least one from a set, the set comprising: skeletal data,visible color data, infra-red color data, and depth data.
 15. The methodof claim 10 wherein the visual representation comprises an overlay ofcolor data corresponding to the captured data and skeletal mapping datacorresponding to the captured data.
 16. The method of claim 10 whereinthe visual output comprises a list of a plurality of gesture filters ofthe application, further comprising: in response to user selection of aselected gesture filter of the plurality of gesture filters, displayingthe visual representation of at least one aspect of the user data, thevisual representation corresponding to the selected gesture filter. 17.The method of claim 10 wherein the visual representation comprises askeletal map of at least part of the user corresponding to the data,further comprising: displaying an indication in the visualrepresentation of at least one part of the skeletal map that correspondsto a selected gesture filter.
 18. The method of claim 10, furthercomprising: storing the data captured by the capture device.
 19. Themethod of claim 10 wherein the visual representation comprises a value,a range of values, or a bound of the parameter.
 20. A computer-readablestorage medium bearing computer-readable instructions that, whenexecuted on a processor, cause the processor to perform operationscomprising: receiving data captured by a capture device, the datacomprising information about user position or movement; displaying avisual output of the application; displaying a visual representation ofat least one aspect of the user data; receiving, via a user interface ofthe display, a change to a parameter of the gesture filter of theapplication; and altering the gesture filter corresponding to thereceived change.